Vincent Sitzmann

Assistant Professor, MIT EECS

Hi, I'm Vincent!

I lead the Scene Representation Group at MIT CSAIL, where we build machines that learn to understand and interact with our world autonomously.

Highlighted Work

See our group website for more publications.

True Self-Supervised Novel View Synthesis is Transferable

Thomas W. Mitchel*, Hyunwoo Ryu*, Vincent Sitzmann

arXiv 2025

Website Code arXiv

Selective Underfitting in Diffusion Models

Kiwhan Song, Jaeyeon Kim, Sitan Chen, Yilun Du, Sham Kakade, Vincent Sitzmann

arXiv 2025

arXiv

Locality in Image Diffusion Models Emerges from Data Statistics

Artem Lukoianov, Chenyang Yuan, Justin Solomon, Vincent Sitzmann

Spotlight • NeurIPS 2025

Website Code arXiv

Controlling diverse robots by inferring Jacobian fields with deep networks

Sizhe Li, Annan Zhang, Boyuan Chen, Hanna Matusik, Chao Liu, Daniela Rus, Vincent Sitzmann

Nature Journal Article • Nature 2025

Paper Website Code Twitter arXiv

History-Guided Video Diffusion

Kiwhan Song*, Boyuan Chen*, Max Simchowitz, Yilun Du, Russ Tedrake, Vincent Sitzmann

ICLR 2025

Website Code Twitter arXiv

Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion

Boyuan Chen, Diego Marti Monso, Yilun Du, Max Simchowitz, Russ Tedrake, Vincent Sitzmann

NeurIPS 2024

Website Code Twitter arXiv

pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstruction

David Charatan, Sizhe Li, Andrea Tagliasacchi, Vincent Sitzmann

Best Paper Runner-Up • CVPR 2023

Website Code Twitter arXiv

Decomposing NeRF for Editing via Feature Field Distillation

Sosuke Kobayashi, Eiichi Matsumoto, Vincent Sitzmann

NeurIPS 2022

Website Code Twitter arXiv

Implicit Neural Representations with Periodic Activation Functions

Vincent Sitzmann*, Julien N. P. Martel*, Alexander W. Bergman, David B. Lindell, Gordon Wetzstein

Oral • NeurIPS 2020

Website Code Twitter arXiv

Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations

Vincent Sitzmann, Michael Zollhoefer, Gordon Wetzstein

Outstanding New Directions - Honorable Mention • NeurIPS 2019

Website Code Twitter arXiv

Blog

Thoughts on research, teaching, and AI. View all posts

Sep 24, 2025

Make It Work, Then Prove It Works: A Framework for Research

There are two disparate skillsets required for good research: moving fast to find what works, then slowing down to prove it. Knowing when to switch between them is crucial.

Teaching

Courses I have taught at MIT.

Advances in Computer Vision

Spring 2025 • 6.8300

Short Biography

Vincent Sitzmann is an Assistant Professor at MIT where he leads the Scene Representation Group. He received his PhD at Stanford University with Gordon Wetzstein and his Bachelor's degree from the Technical University of Munich. Vincent's research goal is to build machines that learn to understand and interact with the world autonomously by building ``world models'' - mental simulators that enable an agent to simulate what will happen next in their environment and as a consequence of their actions, a critical piece of AI and key in downstream applications in graphics, vision, and robotics.